Generative AI is perched on the peak of inflated expectations in Gartner’s 2023 hype cycle for emerging technologies released Wednesday.
With most of the hype now behind artificial intelligence, Gartner is predicting the technology will deliver transformational benefits in two to five years.
“The popularity of many new AI techniques will have a profound impact on business and society,” Gartner Vice President Analyst Arun Chandrasekaran said in a statement.
“The massive pretraining and scale of AI foundation models, viral adoption of conversational agents, and the proliferation of generative AI applications are heralding a new wave of workforce productivity and machine creativity,” he added.
Gartner’s Hype Cycle for Emerging Technologies report is a distillation of more than 2,000 technologies and applied frameworks that the firm profiles annually into a set of “must-know” emerging technologies that have the potential to deliver transformational benefits in the next two to 10 years.
“While all eyes are on AI right now, CIOs and CTOs must also turn their attention to other emerging technologies with transformational potential,” Gartner Vice President Analyst Melissa Davis explained in a statement.
“This includes technologies,” she continued, “that are enhancing developer experience, driving innovation through the pervasive cloud, and delivering human-centric security and privacy.”
Emerging AI Tech
Although generative AI is attracting a lot of attention at present, Gartner’s report noted that some emerging AI techniques offer immense potential for enhancing the experiences of digital customers, allowing them to make better business decisions and build sustainable competitive differentiation.
Emerging AI technologies cited in the report include AI simulation, causal AI, federated machine learning, graph data science, neuro-symbolic AI, and reinforcement learning.
“There are many forms of AI beyond generative AI,” noted Mark N. Vena, president and principal analyst at SmartTech Research in San Jose, Calif.
“Each of these forms of AI has the potential to impact how we live, work, and do business in different ways,” he told TechNewsWorld. “For example, machine learning can help businesses make better decisions by analyzing large amounts of data and identifying patterns that humans might miss.”
“The popularity of new AI techniques will indeed have a profound impact — and already has — on business and society,” added Luciano Allegro, co-founder and CMO of BforeAI, a threat intelligence company, in Montpellier, France.
One domain where that’s evident is cybersecurity. “We’ve already seen improvements in cyberattacks, such as impersonation and phishing using AI-driven techniques to do the heavy lifting,” Allegro told TechNewsWorld. “Those techniques may include building faster, better emails and websites in multiple languages that look and behave exactly like the original, trusted source.”
Boosting Developer Experience
Gartner also called out in its report technologies that enhance a software developer’s experience. DevX refers to all aspects of interactions between developers and the tools, platforms, processes, and people they work with to develop and deliver software products and services, the report explained.
It noted that enhancing DevX is critical to the success of most enterprises’ digital initiatives. “That’s absolutely true and has been for a long time,” said Larry Maccherone, a DevSecOps transformation evangelist at Contrast Security, a maker of self-protecting software solutions in Los Altos, Calif.
“It’s a way to attract and retain top talent,” he told TechNewsWorld.
Key technologies enhancing DevX cited by Gartner include AI-augmented software engineering, API-centric SaaS, GitOps, internal developer portals, open-source program office, and value stream management platforms.
“Applying generative AI to developer tools is massively speeding up code creation,” Rob Enderle, president and principal analyst with the Enderle Group, an advisory services firm in Bend, Ore., told TechNewsWorld.
Maccherone explained improvements for software developers usually emerge in one of two forms: they either lower the cost of coordination, so more people can work on a project without their productivity being swamped by communications costs, or they introduce a new cognitive prosthetic, which allows a single mind to be more efficient.
“Right now, the cognitive prosthetic improvement is AI,” he said. “I’ve used AI for about a year and a half now, and I’m two to three times more productive because of AI.”
Cloud vs. On-Prem DevX Challenge
Andrew Moloney, chief strategy officer for Softiron, a designer, manufacturer, and seller of data infrastructure products in London, maintained that the cloud-first/cloud-native model is where most larger organizations are at.
“What’s key though — and this applies to the challenge of delivering on DevX as well — is don’t equate that merely to deploying in public clouds,” he told TechNewsWorld.
“It’s well understood that the majority of organizations today have very significant workloads that just don’t, and may never, work in the public cloud and need to live on-prem,” he continued.
“What will be needed is investment to recreate that developer experience in private clouds — delivering the API-first, cloud-native, consumption experience that Gartner identifies,” he said.
“In fact,” Moloney added, “in the time horizon of this hype cycle, those that don’t will, in my opinion, struggle to find any engineers left willing to work any other way.”
The report also predicted that over the next 10 years, cloud computing will evolve from a technology innovation platform to become pervasive and an essential driver of business innovation.
“I would argue that it has already evolved into a business innovation platform because much of IT moved their business server operations to the cloud years ago, and that is now where much of the development for business apps and innovation is occurring,” Enderle contended.
Gartner explained that to enable the pervasive adoption of cloud computing the technology will become more distributed and focus on vertical industries. It added that maximizing value from cloud investments will require automated operational scaling, access to cloud-native platform tools, and adequate governance.
Technologies identified by Gartner as key to enabling the pervasive cloud include augmented FinOps, cloud development environments, cloud sustainability, cloud-native, cloud-out to edge, industry cloud platforms, and WebAssembly (Wasm).
Human-Centric Security and Privacy
Gartner also predicted that organizations would look to strengthen their resiliency through technologies that allow them to weave a security and privacy fabric into their digital design through human-centric security and privacy programs.
“It is an interesting concept that goes back to the beginning of cybersecurity in the 1950s when virtually all of the security problems were human-sourced,” Enderle said.
“Companies begin to rely too much on technology and not enough on human training, drills, and penetration testing to assure human compliance with security protocols,” he added.
Gartner noted that numerous emerging technologies are enabling enterprises to create a culture of mutual trust and awareness of shared risks in decision-making between many teams.
Among the technologies supporting the expansion of human-centric security and privacy cited by Gartner were AI TRiSM, cybersecurity mesh architecture, generative cybersecurity AI, homomorphic encryption, and postquantum cryptography.
“In cybersecurity, we need to move beyond ‘awareness,'” observed Karen Walsh, CEO of Allegro Solutions, a cybersecurity consulting company in West Hartford, Conn.
“Awareness means that people have heard of a problem,” she told TechNewsWorld. “We need to move toward education aimed at changing behaviors. Gartner identifies one of the key technologies as AI trust, risk, and security management (TRiSM), which will be critical for all companies.”
For organizations eager to adopt emerging technologies, Gartner’s Davis had a warning. “As the technologies in this Hype Cycle are still at an early stage, there is significant uncertainty about how they will evolve,” she noted. “Such embryonic technologies present greater risks for deployment, but potentially greater benefits for early adopters.”